Metabolomics 4 Flashcards
Pharmacometabonomics - definitions
-> personalized medicine
Personalized medicine: “Application of genomic and molecular data to better target the delivery of healthcare, facilitate the discovery and clinical testing of new products, and help determine a person’s predisposition to a particular disease or condition” (Abrahams 2005)
= precision medicine, stratified medicine, or individualized medicine
Simpler: “the use of genomic, molecular, and clinical information to select medicines that are more likely to be both effective and safe for that patient” (Everett 2016)
Pharmacometabonomics - definitions
-> Pharmacogenomics
Pharmacogenomics is the study of how genetic variation modulates drug responses between individuals and evidence has accumulated of the involvement of over 2000 genes in drug responses (Salari et al., 2012).
Why pharmacometabolomics may struggle:
1) Drug absorption, metabolism, and excretion will be subject to environmental factors such as diet, the use of alcohol, the taking of other medications, and the status of the patient’s microbiome
2) Genetic differences between patients indicate that there may be alterations in the downstream metabolic phenotype. There is not always a fixed relationship between altered genotype and expression of phenotype
3) Phenoconversion: mismatch between the genotype-based prediction of drug metabolism and the true capacity of an individual to metabolize drugs (phenotype) due to the presence of non-genetic factors (comorbidities, drug-drug interactions that influence metabolism).
Pharmaco-metabonomic phenotyping and personalized drug treatment
… specific case where the intervention is drug treatment and the prediction is of drug outcome in terms of differential drug pharmacokinetics (PK), metabolism, safety, or efficacy among the subjects in the cohort, where the prediction is made on the basis of an analysis of the differential pre-dose metabolic profiles in that same cohort.
Pharmacometabolomics - interactions
Metabolic and other individual characteristics influence:
- Metabolite profiles of pre-dose bio fluids
- inter subject variation in effects of drugs
Initial study. prepose profiles in rats
Rat urine predose urine metabolomics profiles before administration of galactosamine hydrochloride (liver toxic,
agent that is sometimes used in animal models of liver failure.
Preliminary study: Predose profiles
Definition of pharmcometabonomics
‘the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures’.
Rat urine predose profiles before administration of galactosamine hydrochloride
The initial pharmacometabolwomics experiment
- Pre- and post-dose urine samples from 65 rats given a single toxic-threshold dose of paracetamol (600 mg kg-1), treatment resulted in no mortality or clinical signs)
- 1H-NMR metabolomics
Major paracetamol-related metabolites:
* paracetamol sulphate (S),
* paracetamol glucuronide (G),
* the mercapturic acid (MA) derived from paracetamol,
* and paracetamol itself (P)
=> G/P ratio shows liver metabolic activity
Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism
Study design: 99 volunteers
500mg dose of paracetamol (acetaminophen, N-acetyl-p-aminophenol)
Pre-dose urine samples
+ post-dose urine over 2 consecutive 3-h periods (0–3 h and 3–6 h after dosing).
Main metabolites of acetaminophen:
- O-sulfonation-> acetaminophen sulfate (S),
- Glucuronidation -> acetaminophen glucuronide (G)
=> Highly relevant S/G ratio
Identification of the biomarker 4-cresylsulfate
The identification of the biomarker as 4-cresylsulfate came as a shock as this is not wholly a human metabolite. It is a bacterial/human co-metabolite that is produced by the human sulfation of 4-cresol, which is itself a metabolite originating in the gut microbiome, particularly from some Chlostridia species of bacteria (Smith and Macfarlane, 1997).
In order to gain confidence in the findings, the entire NMR analysis was repeated in 2007, 4 years after the original analysis but using NMR tubes instead of a flow probe: no significant changes to the results were found. In addition, in 2008, the original NMR-based analysis of S/G for the 3–6 h post-dose urines was repeated using UPLC-MS with a correlation coefficient of 0.99 and no outliers (quantitation from online UV detector).
- Urinary levels of p-cresol-sulfate (PCS) and phenylacetylglutamine (PAG) were found to be broadly correlated, only PCS was likely to provide statistically significant discrimination with respect to S/G
- If the pre-dose ratio of p-cresol normalized to creatinine was >0.06, then the post-dose ratio of S/G was always <0.8.
- However, if the pre-dose ratio of PCS, normalized to creatinine was <0.06, then the post-dose ratio of S/G took a wide range of values and was not predictable. A
Why is prepose PCS a marker for effective acetaminophen metabolism?
-> Hypothesis
Hypothesis: There could be a metabolic mechanism that affects both endogenous (p-cresol) and drug metabolism
- Mice and rats that can metabolite 4-cresol by sulfation or glucuronidation,
- humans metabolize 4-cresol largely by sulfation.
- In a person with a gut microbiome excreting large amounts of 4-cresol, the sulfation of this toxin to 4-cresylsulfate, metabolite 4, may use up a large part of the limited sulfation capacity of that individual.
- If that person is subsequently challenged with a large dose of a drug, such as paracetamol, requiring metabolism
by sulfation, then the body will use glucuronidation to a greater extent instead, to make up for its diminished sulfation capacity.
Why is prepose PCS a marker for effective acetaminophen metabolism?
-> Answer
Answer: Same metabolic mechanism For endogenous and drug metabolism
Person with a gut microbiome excreting large amounts of 4- cresol, the sulfonation to 4- cresylsulfate uses up a large part of the limited sulfonation capacity of that individual.
If that person is subsequently challenged with a large dose of paracetamol, requiring metabolism by sulfonation, then the body will use glucuronidation to a greater extent, to make up for its diminished sulfonation capacity
Particularly acute for paracetamol and 4-cresol:
- utilize the same sulfotransferase enzyme co-factor, 3ʹ- phosphoadenosine 5ʹ- phosphosulfate, which is in limited supply
- also in competition for the same sulfotransferase enzyme (SULT1A1)
P-cresol and acetaminophen Sulfonation by PAPS 3’-phosphoadenosine 5’-phosphosulfate = limiting factor
Purine pathway implicated in mechanism of resistance to aspirin therapy: Pharmacometabolomics-informed Pharmacogenomics
- purines were associated with aspirin response and poor responders had higher postaspirin adenosine and inosine levels than did good responders
Human metabolic individuality in biomedical and pharmaceutical research
- Metabolic profiling was done on fasting serum from participants in the German KORA F4 study (n 5 1,768) and the British TwinsUK study (n= 1,052),
- using ultrahigh-performance liquid-phase chromato- graphy and gas- chromatography separation, coupled with tandem mass spectrometry.
- Achieved highly efficient profiling (24 min per sample) with low median process variability (<12%) of more than 250 metabolites, covering more than 60 biochemical pathways of human metabolism
Proton NMR analysis of plasma is a weak predictor of coronary artery disease
The predictive power for CAD was substantially higher than predictions based on conventional risk factors using the same multivariate methods to process and model the data as for the 1H-NMR spectra. The predictive power of the 1H-NMR spectra analysis, however, did not approach the 99% accuracy with a confidence limit of 99% that would be required of a potential replacement for angiography, contrary to the suggestion in the previous study that this might be possible. The usefulness of the technique, if the limitations described here are overcome by larger studies and more sophisticated analyses, might be as an additional risk assessment of clinically silent disease for noninvasive population screening.
Lipids, Lipoproteins, and metabolites and risk of myocardial infarction and stroke
- China Kadoorie Biobank (CKB), prospective cohort of 512,891 Chinese adults 30 to 79 years of age at enrolment
- A subset of 4,662 individuals was selected for the metabolomics study from a larger nested case-control study of stroke and CHD subtypes comprising 23,000 CKB individuals
- 137 run in duplicate
- Spectra from which 225 lipid and other metabolic measures were simultaneously quantified
-> Very low-, intermediate- and low-density lipoprotein particles were positively associated with MI and IS. High-density lipoprotein (HDL) particles were inversely associated with MI apart from small HDL. In contrast, no lips-protein particles were associated with ICH. Cholesterol in large HDL was inversely associated with MI and IS, whereas cholesterol in small HDL was not. Triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI, with a similar pattern for IS. Glycoprotein acetals, ketone bodies, glucose and docosahexaenoic acid were associated with all 3 diseases. The 225 metabolic markers showed concordant associations between MI and IS, but not with ICH.
-> Lipoproteins and lipids showed similar associations with MI and IS, but not with ICH. Within HDL particles, cholesterol concentrations were inversely associated, whereas triglyceride concentrations were positively associated with MI. Glycoprotein acetals and several non-lipid related metabolites associated with all 3 diseases.
